The Use of Topical Tacrolimus as Adjunct Therapy to Corticosteroid in a High-Risk Penetrating Keratoplasty: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Purpose: To evaluate the use of topical tacrolimus as an adjunct therapy to corticosteroids in preventing graft rejection in high-risk penetrating keratoplasty (PKP). Methods: A comprehensive search was conducted through PubMed ® , EMBASE ® , Cochrane Central Register of Controlled Trials, and Google Scholar ® databases from 2000 to 2023. Eligible studies included meta-analysis, systematic review, clinical trial, and case presentations that compared graft rejection rates in high-risk PKP patients treated with corticosteroid versus corticosteroid plus tacrolimus. Studies with a control group using noncorticosteroid therapy were excluded from the study. The study selection process followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study quality was assessed using Cochrane Risk of Bias 2.0 (RoB 2.0), Newcastle–Ottawa Scale, and RoB for Nonrandomized Intervention Studies. Results: Five studies comprising 298 eyes were included in the study. Rejection rates were found significantly lower in the tacrolimus group (RR: 0.63; 95% confidence interval [CI]: 0.46–0.88; P = 0.006). Tacrolimus also significantly reduced irreversible rejection (RR: 0.50; 95% CI: 0.27–0.93; P = 0.03) and improved visual acuity (RR: 1.45; 95% CI: 1.08–1.93; P = 0.01). Conclusions: Tacrolimus successfully reduces the rejection rate and irreversible rejection in high-risk PKP patients. Improved visual acuity was observed. There were no significant side effects; however, further studies are still needed to achieve more quantitative results, like recommended concentrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it